- Define and own Fetch’s company-level measurement framework
- Establish decision frameworks for pricing, incentives, and value trade-offs
- Set standards for evidence quality, uncertainty, and confidence
- Define the causal reasoning model used across departments
- Own the scientific capability roadmap
- Architect the semantic mart and metric logic powering FetchGPT
- Define canonical metric definitions and unify logic
- Partner with engineering to build foundational data assets
- Establish BI standards
- Serve as the quality bar for high-impact analytics
- Review strategic analyses
- Set scientific rules for experimentation
- Ensure observational and experimental results reconcile
- Create templates and interpretation guides
- Own cross-company models including marketing mix, elasticity, and forecasting
- Raise the scientific maturity of the data science organization
- Design upskilling programs
- Author best-practice modeling libraries
- Serve as a technical anchor and thought partner
- Establish norms for rigorous, transparent insights
- Apply advanced statistical and causal methods
- Build scalable, production-ready analytical frameworks
- Champion best practices in experimentation design, model validation, and reproducibility
- Leverage modern analytics tooling such as Python, SQL, Snowflake, dbt, and experimentation platforms
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